{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 机器学习在时间序列预测中的应用"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "机器学习（Machine Learning）是人工智能（AI）中很重要的一部分，在目前的实践过程中，大多数人工智能问题是由机器学习的方式实现的。目前机器学习已经广泛应用于数据挖掘、计算机视觉、自然语言处理、语音和手写识别、生物特征识别、医学诊断、检测信用卡欺诈、证券市场分析、搜索引擎、DNA序列测序、无人驾驶、机器人等领域。机器学习算法有很多，有分类、回归、聚类、推荐、图像识别领域等等，具体算法比如线性回归、逻辑回归、朴素贝叶斯、随机森林、支持向量机、神经网络等等。在机器学习算法中，没有最好的算法，只有“更适合”解决当前任务的算法。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果按照学习方式分类可分为监督式学习、非监督式学习、半监督式学习和增强学习。其中有监督学习训练集目标:有标注; 如回归分析，统计分类；无监督学习训练集目标:无标注;如聚类、GAN(生成对抗网络)；半监督式学习介于监督式与无监督式之间；增强学习则是智能体不断与环境进行交互，通过试错的方式来获得最佳策略。如果按照学习任务分类可分为以下三类：分类、回归和聚类。其中分类是预测一个标签 （是离散的），属于监督学习；回归是预测一个数量 （是连续的），属于监督学习；聚类属于无监督学习。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "分类方法是一种对离散型随机变量建模或预测的监督学习方法。其中分类学习的目的是从给定的人工标注的分类训练样本数据集中学习出一个分类函数或者分类模型，也常常称作分类器（classifier）。当新的数据到来时，可以根据这个函数进行预测，将新数据项映射到给定类别中的某一个类中。\n",
    "\n",
    "对于分类，输入的训练数据包含信息有特征（Feature），也称为属性（Attribute），有标签（label）,也常称之为类别（class），具体可表示为（F1，F2，...Fn; label）。而所谓的学习，其本质就是找到特征与标签间的关系（mapping 即映射） 。所以说分类预测模型是求取一个从输入变量 (特征)  到离散的输出变量（标签） 之间的映射函数。这样当有特征而无标签的未知数据输入时，可以通过映射函数预测未知数据的标签。\n",
    "\n",
    "简单地说，分类就是按照某种标准给对象贴标签，再根据标签来区分归类。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "分类方法常用的有Logistic 回归、线性判别法、 二次判别分析、朴素贝叶斯、分类树、支持向量机 （Support Vector Machine）、KNN（K-Nearest Negihbour）、集成学习（Ensembale Learning，包括随机森林）、深度学习（Deep Learning）等等。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 逻辑回归Logistic Regression（LR）\n",
    "\n",
    "本文将使用LR来衡量二进制分类因变量（“向上”或“向下”）与多个独立连续变量（滞后百分比返回）之间的关系。该模型提供了将特定（以下）日期分类为“上”或“下”的概率。 在此实现中，如果概率超过0.5，我们选择将每天指定为“最多”。可以使用其他阈值，但为简单起见，我选择了0.5。\n",
    "\n",
    "假设L1,L2,...Ln为预测因子，LR模型使用对数公式对上涨(U)的条件概率建立以下模型：\n",
    "\n",
    "$$P(Y=U|L_1,L_2,...,L_n)=\\frac{e^{\\beta_0+\\beta_1L_1+\\beta_2L_2+...+\\beta_nL_n}}{1+e^{\\beta_0+\\beta_1L_1+\\beta_2L_2+...+\\beta_nL_n}}$$\n",
    "使用逻辑回归是因为它为L1和L2的所有值提供[0,1]之间的概率，这与线性回归不同，线性回归可以在相同的设置中生成负概率。\n",
    "为了拟合模型（即，估计βi系数），使用最大似然法。scikit-learn库可以实现LR模型的拟合和预测。\n",
    "\n",
    "## 线性判别法Linear Discriminant Analysis （LDA）\n",
    "\n",
    "LDA与LR的区别在于，LR使用对数函数将$P(Y=U|L_1,L_2)$建模为给定预测变量Li的响应Y的条件分布；在LDA中，给定Y，分别对Li变量的分布进行建模，并通过贝叶斯定理获得$P(Y=U|L_1,L_2)$。\n",
    "\n",
    "本质上，LDA是通过假设预测变量来自多元高斯分布得出的。 在计算出该分布的参数的估计值之后，可以将这些参数输入贝叶斯定理中，以便对观测值属于哪个类别做出预测。LDA假定所有类别共享相同的协方差矩阵。由于scikit-learn提供了拟合和预测方法，因此我不会过多地考虑进行预测所需的分布或后验概率的公式。\n",
    "\n",
    "## 二次判别分析Quadratic Discriminant Analysis （QDA）\n",
    "\n",
    "二次判别分析（QDA）与LDA密切相关。显着的区别在于，每个类别现在都可以拥有自己的协方差矩阵。当决策边界为非线性时，QDA通常会表现更好。LDA通常在训练观察次数较少时（即需要减少方差时）表现更好。另一方面，当训练集较大时（即，差异较小，则QDA表现良好）。一个或另一个的使用最终归结为偏差方差的权衡。与LR和LDA一样，scikit-learn负责QDA的实现，因此我们只需要为它提供训练/测试数据即可进行参数估计和预测。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 预测准确率指标"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们根据指数收益率的正负划分为上涨（1）和下跌（-1）两种类型，然后利用前N日的收益率数据对当日上涨、下跌概率进行预测。\n",
    "衡量预测准确率的方法有很多，包括均方差（Mean-Squared Error,MSE）、平均绝对离差（Mean Absolute Deviation，MAD）和均方根误差（Root-Mean-Squared Error,RMSE）等。本文关注的是Hit rate指标，衡量预测准确次数的百分比。 在后面的示例中，将进一步使用混淆矩阵来逐步评价预测性能。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "预测因子的选择，与预测方法的选择一样重要，对预测性能起到决定性作用。预测股市指数回报时，有很多潜在因素可供选择。由于本文的目的是为了展示预测的过程而非结果，为了简便起见，本文只利用指数回报的滞后值作为预测因子。尽管有可用的统计检验可以证明每个因素的预测能力，但是通常最好在模型中使用较少的预测因子。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T13:52:01.123812Z",
     "start_time": "2019-11-01T13:52:01.054461Z"
    }
   },
   "outputs": [],
   "source": [
    "#先引入后面可能用到的包（package）\n",
    "import pandas as pd  \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns  \n",
    "sns.set()  \n",
    "%matplotlib inline   \n",
    "\n",
    "#正常显示画图时出现的中文和负号\n",
    "from pylab import mpl\n",
    "mpl.rcParams['font.sans-serif']=['SimHei']\n",
    "mpl.rcParams['axes.unicode_minus']=False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T02:44:03.522856Z",
     "start_time": "2019-11-01T02:44:02.076643Z"
    }
   },
   "source": [
    "### 获取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T12:47:23.341825Z",
     "start_time": "2019-11-01T12:47:23.020059Z"
    }
   },
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'yfinance'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-2-6ab2e44902b5>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mdatetime\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0myfinance\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0myf\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mget_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstocks\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mend_date\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[1;34m'''stocks为股票代码和简称字典'''\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m     \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'yfinance'"
     ]
    }
   ],
   "source": [
    "import datetime\n",
    "import yfinance as yf\n",
    "def get_data(stocks,start_date,end_date):\n",
    "    '''stocks为股票代码和简称字典'''\n",
    "    data=pd.DataFrame()\n",
    "    for code,name in stocks.items():\n",
    "        dd = yf.Ticker(code)\n",
    "        data[name]=dd.history(start=start_date,end=end_date)['Close']\n",
    "    data=data.iloc[2:,:].fillna(method='ffill')\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T12:47:25.519760Z",
     "start_time": "2019-11-01T12:47:25.497852Z"
    }
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'get_data' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-79c816e527c6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[0mstart_date\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'2008-01-01'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[0mend_date\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'2019-10-31'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 12\u001b[1;33m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mget_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mStockIndexs\u001b[0m \u001b[1;33m,\u001b[0m\u001b[0mstart_date\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mend_date\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     13\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'get_data' is not defined"
     ]
    }
   ],
   "source": [
    "StockIndexs = {\n",
    "    '000001.SS':'上证综指',\n",
    "    '^DJI':'道琼斯',\n",
    "    '^IXIC':'纳斯达克',\n",
    "    '^N225':'日经225',\n",
    "    '^HSI' :'香港恒生',\n",
    "    '^FCHI':'法国CAC40', \n",
    "    '^GDAXI':'德国DAX'}\n",
    "#获取数据\n",
    "start_date='2008-01-01'\n",
    "end_date='2019-10-31'\n",
    "data=get_data(StockIndexs ,start_date,end_date)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T07:28:24.055756Z",
     "start_time": "2019-11-01T07:28:23.631892Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#累计收益率\n",
    "(data/data.iloc[0]).plot(figsize=(14,6))\n",
    "plt.title('全球主要指数累计净值\\n (2008-2019)',size=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T07:28:32.085915Z",
     "start_time": "2019-11-01T07:28:31.524412Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#收益率相关性\n",
    "ret=data.apply(lambda x : (x/x.shift(1)-1)*100).dropna()\n",
    "sns.clustermap(ret.corr())\n",
    "plt.title('全球主要指数相关性',size=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T07:28:44.440063Z",
     "start_time": "2019-11-01T07:28:44.427098Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_variables(ret):\n",
    "    '''ret为上述指数收益率数据'''\n",
    "    df=pd.DataFrame()\n",
    "    df['lag1']=ret['上证综指'].shift(1)\n",
    "    df['lag2']=ret['上证综指'].shift(2)\n",
    "    df['DJ']=ret['道琼斯'].shift(1)\n",
    "    df['DA']=ret['德国DAX'].shift(1)\n",
    "    df['RJ']=ret['日经225'].shift(1)\n",
    "    #上涨用1表示，下跌（含0）为-1\n",
    "    df['direction']=np.where(ret['上证综指'].values>0,1.0,-1.0)\n",
    "    df=df.dropna()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T08:00:02.348983Z",
     "start_time": "2019-11-01T08:00:02.339010Z"
    }
   },
   "outputs": [],
   "source": [
    "#引入机器学习库\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\n",
    "from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis as QDA\n",
    "from sklearn.metrics import accuracy_score,classification_report,confusion_matrix,roc_curve\n",
    "def fit_model(name, model, X_train, y_train, X_test, pred):\n",
    "    \"\"\"使用LR, LDA 、QDA对数据进行模型拟合\n",
    "    \"\"\"\n",
    "    # Fit and predict the model on the training, and then test, data\n",
    "    model.fit(X_train, y_train)\n",
    "    pred[name] = model.predict(X_test)\n",
    "    # 预测准确率\n",
    "    score=accuracy_score(pred['Actual'], pred[name])\n",
    "    print(\"%s模型: %.3f\" % (name, score)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T08:00:04.843406Z",
     "start_time": "2019-11-01T08:00:04.774580Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "预测准确率:\n",
      "LR模型: 0.557\n",
      "LDA模型: 0.566\n",
      "QDA模型: 0.590\n"
     ]
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    #获取数据\n",
    "    variables = get_variables(ret).loc[:'2017']\n",
    "    # 涨跌方向为响应变量, 其余变量为自变量\n",
    "    X = variables.iloc[:,:-1]\n",
    "    y = variables.iloc[:,-1]\n",
    "    # 把原始数据的40%作为测试数据，其余为训练数据\n",
    "    #X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.4)\n",
    "    #以2017年以前数据为训练集，2017年数据为测试集\n",
    "    \n",
    "    start_test = datetime.datetime(2017,1,1)\n",
    "    X_train = X[X.index < start_test]\n",
    "    X_test = X[X.index >= start_test]\n",
    "    y_train = y[y.index < start_test]\n",
    "    y_test = y[y.index >= start_test]\n",
    "    # 创建预测数据框\n",
    "    pred = pd.DataFrame(index=y_test.index)\n",
    "    pred[\"Actual\"] = y_test\n",
    "    # 分别拟合LR, LDA 和QDA三个模型  \n",
    "    print (\"预测准确率:\")\n",
    "    models = [(\"LR\", LogisticRegression(solver='liblinear')), (\"LDA\", LDA()), (\"QDA\", QDA())]\n",
    "    for m in models:\n",
    "        fit_model(m[0], m[1], X_train, y_train, X_test, pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T08:00:05.739301Z",
     "start_time": "2019-11-01T08:00:05.701401Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>col_0</th>\n",
       "      <th>-1.0</th>\n",
       "      <th>1.0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>direction</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>-1.0</th>\n",
       "      <td>3</td>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>2</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "col_0      -1.0   1.0\n",
       "direction            \n",
       "-1.0          3    98\n",
       " 1.0          2   141"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model=QDA()\n",
    "model.fit(X_train, y_train)\n",
    "# 模型在测试数据集上的预测\n",
    "pred = model.predict(X_test)\n",
    "# 构建混淆矩阵\n",
    "cm = pd.crosstab(y_test,pred)\n",
    "cm\n",
    "# 绘制混淆矩阵图\n",
    "#sns.heatmap(cm, annot = True, cmap = 'GnBu', fmt = 'd')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T08:00:06.534038Z",
     "start_time": "2019-11-01T08:00:06.518113Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "模型的准确率为：\n",
      " 0.5901639344262295\n",
      "模型的评估报告：\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "        -1.0       0.60      0.03      0.06       101\n",
      "         1.0       0.59      0.99      0.74       143\n",
      "\n",
      "    accuracy                           0.59       244\n",
      "   macro avg       0.59      0.51      0.40       244\n",
      "weighted avg       0.59      0.59      0.46       244\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('模型的准确率为：\\n',accuracy_score(y_test, pred))\n",
    "print('模型的评估报告：\\n',classification_report(y_test, pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-01T08:00:07.526947Z",
     "start_time": "2019-11-01T08:00:07.260621Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 计算正例的预测概率，而非实际的预测值，用于生成ROC曲线的数据\n",
    "y_score = model.predict_proba(X_test)[:,1]\n",
    "#fpr表示1-Specificity,tpr表示Sensitivity\n",
    "fpr,tpr,threshold = roc_curve(y_test, y_score)\n",
    "# 计算AUC的值\n",
    "roc_auc = metrics.auc(fpr,tpr)\n",
    "# 绘制面积图\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.stackplot(fpr, tpr, color='steelblue', alpha = 0.5, edgecolor = 'black')\n",
    "plt.plot(fpr, tpr, color='black', lw = 1)\n",
    "# 添加对角线\n",
    "plt.plot([0,1],[0,1], color = 'red', linestyle = '--')\n",
    "# 添加文本信息\n",
    "plt.text(0.5,0.3,'ROC曲线 (area = %0.2f)' % roc_auc)\n",
    "# 添加x轴与y轴标签\n",
    "plt.title('QDA模型预测指数涨跌的ROC曲线',size=15)\n",
    "plt.xlabel('1-Specificity')\n",
    "plt.ylabel('Sensitivity')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "quantstart:\n",
    "\n",
    "[Forecasting Financial Time Series - Part I](https://www.quantstart.com/articles/Forecasting-Financial-Time-Series-Part-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
